Table 2.

Best models for each of the working hypothesis selected according to the model’s AICc and ΔAICc. The hypotheses and models with the higher support (and lower AICc values) are presented in bold.

Models	df	AICc	ΔAICc	AICc weight
H1 - productivity/food resources availability hypothesis
NDVI + Rabbit_abundance	3	65.20	0.00	0.419
NDVI	2	65.34	0.14	0.392
Rabbit_abundance	2	66.79	1.59	0.189
H2 - Disturbance hypothesis
Road_network	2	67.04	0.00	1.000
H3 - Life-history traits hypothesis
Body_size + Age	3	61.67	0.00	0.162
Body_size + Age + Mongoose_dens	4	61.67	0.00	0.162
Age + Mongoose_dens	3	61.98	0.31	0.138
Age	2	62.03	0.36	0.135
Gender + Body_size + Age	4	62.97	1.30	0.085
Gender + Body_size + Age + Mongoose_dens	5	63.00	1.33	0.083
Gender + Age + Mongoose_dens	4	63.24	1.57	0.074
Gender + Age	3	63.26	1.59	0.073
H4 - Climate and orography hypothesis
Altimetry + Annual_rainfall + Annual_temp_range + River_network	5	55.87	0.00	0.542
Altimetry + Annual_rainfall + Annual_temp_range	4	57.61	1.74	0.227
H5 – Cattle farm hypothesis
Dens_cattle_farm	2	66.84	0.00	1.000

df - degrees of freedom. AICc - Akaike’s information criterion. ΔAICc - difference to the lowest AICc value; AICc weight - Akaike weights. Rabbit_abundance - Abundance of wild rabbits; NDVI - Normalized Difference Vegetation Index; Road_network - road network density; Body_size – First component of the Principal component analysis (PCA) of body size (based on weight, snout-tail length, neck perimeter); Mongoose_dens – Egyptian mongoose abundance; Annual_temp_range - annual temperature range.